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Cortical Bone Assessment Using Ultrasonic Guided Waves: A Reproducibility Study in a Healthy Population
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Improvement of a Green's Function Estimation for a Moving Source Using the Waveguide Invariant Theory.

Daehwan Kim1, Donghyeon Kim2, Gihoon Byun3

  • 1Department of Ocean Engineering, Korea Maritime and Ocean University, Busan 49112, Republic of Korea.

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Summary

This study improves underwater sound channel characterization by enhancing the signal-to-noise ratio of broadband Green's functions. The new method uses waveguide invariant and ray-based blind deconvolution for moving sources in shallow water.

Keywords:
Green’s functionray-based blind deconvolutionwaveguide invariant

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Area of Science:

  • Ocean acoustics
  • Signal processing
  • Remote sensing

Background:

  • Underwater sound channel characterization is vital for remote sensing.
  • Traditional methods for estimating channel impulse response (CIR) are computationally intensive.
  • Ray-based blind deconvolution (RBD) is a less demanding alternative but struggles with noise.

Purpose of the Study:

  • To introduce a novel method for improving the signal-to-noise ratio (SNR) of broadband Green's functions.
  • To enable accurate estimation for moving sources without prior range knowledge.
  • To overcome noise limitations in traditional RBD techniques.

Main Methods:

  • Utilizing the waveguide invariant to enhance SNR.
  • Applying RBD with plane-wave beamforming to estimate Green's functions.
  • Coherently combining Green's functions at adjacent ranges using frequency shifts from striation slopes.

Main Results:

  • Significantly improved SNR of broadband Green's functions.
  • Successful demonstration via simulation and real-world shallow water noise data.
  • Effective characterization of underwater sound channels for moving sources.

Conclusions:

  • The proposed method effectively improves Green's function estimation in noisy underwater environments.
  • Waveguide invariant and RBD offer a robust approach for underwater acoustic channel characterization.
  • This technique advances remote sensing applications by providing more reliable acoustic data.